China, as the primary importer of Thailand’s high-quality rice (Oryza sativa L.), has an urgent need for effective origin discrimination methods between premium aromatic rice from China and Thailand to prevent origin mislabeling issues. In this study, stable isotope and elemental multivariate analysis combined with partial least squares discriminant analysis (PLS-DA) were used to build an origin traceability model for Chinese and Thai rice from different production areas. Multivariate analysis of variance revealed that Thai rice exhibited significantly higher δ¹³C (−26.4 ± 0.4‰) and δ¹⁸O (25.9 ± 1.1‰) values, but a significantly lower δ¹⁵N value (3.5 ± 0.8‰) compared to the three major producing regions of China. These differences are directly related to geographical and climatic factors such as latitude, precipitation, and temperature. A PLS-DA model demonstrated high performance in the classification of different Chinese indica rice and Thailand rice origins. Through cross-validation, the classification accuracy for the training set reached 97.3%. For the independent testing set, the classification accuracy was recorded to be 95.0%. Furthermore, external blind sample verification was conducted, and the classification accuracy achieved was 100%. Ca, K, Na, δ¹⁸O, Zn and δ²H were found to be important variables to discriminate between Chinese indica rice and Thai rice. Finally, for country of origin labelling claims, this rice study provides the basis for a suitable regulatory method to detect mislabeled Thai origin rice and prevent fraud.

This study used locally sourced black, red, and white quinoa from Zhangjiakou as experimental materials to optimize the preparation process of quinoa antioxidant peptides and identify their sequence characteristics. Protein was extracted using the alkali-soluble acid precipitation method. The optimal hydrolytic enzyme was selected by comparing the hydrolysis effects of eight proteases. Enzymatic hydrolysis conditions were optimized using single-factor experiments and response surface methodology. After purification by Sephadex G-15 gel filtration chromatography, peptide sequences were identified by liquid chromatography–tandem mass spectrometry (LC-MS/MS) combined with De novo sequencing technology. The results showed that black quinoa and alcalase were identified as the optimal raw material and hydrolytic enzyme, respectively. The optimal enzymatic hydrolysis conditions were an enzyme dosage of 4000 U·g⁻¹, hydrolysis time of 3.5 h, temperature of 42 °C, and pH 7.6, under which the average DPPH radical scavenging rate reached 86.61%. The purified G-1 fraction exhibited the highest antioxidant activity. A total of 1549 peptide sequences with confidence ≥90% were identified, among which peptides containing two or more hydrophobic amino acids accounted for 60.62%. This compositional feature is consistent with structural characteristics commonly associated with antioxidant peptides. This study provides a reference for the processing of quinoa-based functional ingredients.